1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | mtc-m16c.sid.inpe.br |
Holder Code | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Repository | sid.inpe.br/mtc-m18@80/2008/09.30.18.04 (restricted access) |
Last Update | 2008:09.30.18.46.05 (UTC) administrator |
Metadata Repository | sid.inpe.br/mtc-m18@80/2008/09.30.18.04.45 |
Metadata Last Update | 2018:06.04.04.05.33 (UTC) administrator |
Secondary Key | INPE-15449-PRE/10183 |
Citation Key | FariasZepkPint:2008:SuVeMa |
Title | A forecast cloud-to-ground lightning system part 2 - Support vector machines preliminary results |
Format | CD-ROM |
Year | 2008 |
Secondary Date | 20080824 |
Access Date | 2024, May 13 |
Secondary Type | PRE CN |
Number of Files | 1 |
Size | 432 KiB |
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2. Context | |
Author | 1 Farias, Wendell Rondinelli Gomes 2 Zepka, Gisele dos Santos 3 Pinto Junior, Osmar |
Resume Identifier | 1 2 3 8JMKD3MGP5W/3C9JJ2E |
Group | 1 DGE-CEA-INPE-MCT-BR 2 DGE-CEA-INPE-MCT-BR 3 DGE-CEA-INPE-MCT-BR |
Affiliation | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) 3 Instituto Nacional de Pesquisas Espaciais (INPE) |
e-Mail Address | deicy@cptec.inpe.br |
Conference Name | Congresso Brasileiro de Meteorologia, 15. |
Conference Location | São Paulo |
Date | 24-29ago |
Book Title | Anais |
Tertiary Type | Artigo |
Organization | SBMET |
History (UTC) | 2008-12-03 14:20:36 :: deicy -> administrator :: 2018-06-04 04:05:33 :: administrator -> marciana :: 2008 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Content Type | External Contribution |
Keywords | support vector machines ETA model lightning forecast |
Abstract | De forma análoga ao estudo que tratou da rede neural artificial este trabalho apresenta um estudo preliminar sobre o desenvolvimento de um sistema de previsão de descargas elétricas através de uma ferramenta matemática de inteligência artificial chamada Support Vector Machines (SVM), baseado em dados de relâmpagos nuvem-solo da Rede Brasileira de Detecção de Descargas Atmosféricas (BrasilDat) e de saídas de análises do modelo ETA. O conjunto de entrada da SVM foi composto por dados horários de relâmpagos e campos de análise de variáveis meteorológicas do modelo ETA, ambos selecionados para a área da Companhia Paulista de Força e Luz CPFL. A saída da previsão é apresentada na forma de um índice, tal como: baixa, média ou alta atividade elétrica. Assim como para a rede neural, a SVM foi capaz de representar de maneira satisfatória os eventos de raios estudados, mesmo sendo as tempestades um fenômeno complexo, devido aos diferentes processos físicos envolvidos na sua formação e evolução. Diante dos resultados encontrados, o uso de ferramentas matemáticas de inteligência artificial como rede neural e SVM indicam serem ferramentas promissoras para a construção de um sistema de previsão de descargas elétricas. ABSTRACT: This work presents a preliminary study about the development of a lightning forecast system based on the Support Vector Machines (SVM) mathematical tool, using cloud-to-ground (CG) lightning data provided by Brazilian Lightning Detection Network (BrasilDat) and analysis output from the ETA model. The work is similar to that presented in paper 1 using a neural network. The dataset input variables was composed by hourly number of lightning flashes and analysis fields of meteorological parameters from ETA model both picked and chosen for Companhia Paulista de Força e Luz CPFL Energy area. The forecasting output is presented in terms of a lightning index as: low, medium and high lightning activity. As well as for NN, the SVM technique has showed able of to represent satisfactorily the lightning events study, despite of the complex phenomenon, because there are many physical processes involved in its formation and evolution, Thereby, the use of techniques of artificial intelligence as NN and SVM indicate to be a promising mathematical tool to build a lightning prediction system. |
Area | FISMAT |
Arrangement | urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDGE > A forecast cloud-to-ground... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | there are no files |
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4. Conditions of access and use | |
Language | en |
Target File | Farias_CBMET2008_parte2.pdf |
User Group | administrator deicy |
Visibility | shown |
Copy Holder | SID/SCD |
Read Permission | deny from all and allow from 150.163 |
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5. Allied materials | |
Next Higher Units | 8JMKD3MGPCW/3EU29DP |
Host Collection | sid.inpe.br/mtc-m18@80/2008/03.17.15.17 |
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6. Notes | |
Empty Fields | archivingpolicy archivist callnumber copyright creatorhistory descriptionlevel dissemination documentstage doi edition editor electronicmailaddress identifier isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup rightsholder schedulinginformation secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |
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7. Description control | |
e-Mail (login) | marciana |
update | |
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